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very challenging. Therefore, high-throughput screening of drug-like molecules needs to also consider their synthetic viability. The aim of this project is to develop a deep learning and generative design
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challenges associated with battery design and manufacturability that will underpin the successful design of new battery systems for future electric vehicles (EVs) and aircraft. Meeting future EV requirements
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forward for fusion research. For UK based researchers the next step is to work towards a direct-driven laser fusion facility. Such a step requires predictive models for laser system and fuel pellet design
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of the manufacturing process is not considered. The discrepancy between the as-designed and as-manufactured geometries may induce non-negligible effects to the predicted quantities of interest. Fewer studies have
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our crowd-sourced databases containing ALD and ALE processes to enable AI-compatible atomic-level processing approaches. It also explores novel avenues for AI-driven process development, material design
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., lasers) to robustly and repeatably induce different battery failure modes beyond to those possible using conventional test methods. This research will (1) provide valuable new insights into battery design
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will investigate the following three main directions: Designing effective WiFi feature templates (e.g., angle of arrival, Doppler frequency shift) to capture human behaviour information while suppressing
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have the potential to inspire new ideas, approaches and innovation and become future leaders in developing new technologies. HetSys builds on Warwick's cross-departmental scientific computing research
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large projects. With its project partners HetSys develops talented PhD students to push boundaries in this exciting field. The students have the potential to inspire new ideas, approaches & innovation
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partners HetSys develops talented PhD students to push boundaries in this exciting field. The students have the potential to inspire new ideas, approaches and innovation and become future leaders in